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A human brain is capable of accessing the emotions by watching the facial expressions. In this paper, machine learning is proposed for six facial expressions namely anger, fear, disgust, happiness, surprise and sadness. This proposed system presents a human emotion recognition model based on facial expressions using geometrical features. The key advantage of these features is that they are independent...
The classification of affective semantics in images is a very challenging research direction that gains more and more attention in the research community. However, as an emerging topic, contributions remain relatively rare, and a lot of issues need to be addressed particularly concerning the three following fundamentals problems: emotion representation, image features used to represent emotions and...
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